Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT.
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| Title: | Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT. |
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| Authors: | Li L; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China., Zhou X; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China.; Department of Radiology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China., Cui W; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China., Li Y; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China., Liu T; Department of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China., Yuan G; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China. yuangang@sibet.ac.cn.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. yuangang@sibet.ac.cn., Peng Y; Department of Medical Imaging, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People's Hospital, Guizhou, 550002, China. pys@mail.ustc.edu.cn., Zheng J; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. |
| Source: | Journal of cancer research and clinical oncology [J Cancer Res Clin Oncol] 2023 Nov; Vol. 149 (17), pp. 15469-15478. Date of Electronic Publication: 2023 Aug 29. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 7902060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1335 (Electronic) Linking ISSN: 01715216 NLM ISO Abbreviation: J Cancer Res Clin Oncol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1432-1335 |
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| DOI: | 10.1007/s00432-023-05329-2 |
